OP0035 WHAT EXPLAINS THE WORLDWIDE GRADIENT OF AGE AT ONSET OF RHEUMATOID ARTHRITIS ALONG LATITUDE? A MULTILEVEL ANALYSIS IN THE METEOR REGISTRY
Authors: S. A. Bergstra, A. Sepriano, A. Chopra, L. L. Winchow, D. Vega-Morales, K. Solomon-Escoto, X. Matthijssen, R. B. M. Landewé
Journal: Annals of the Rheumatic Diseases (2022)

Background It has been suggested that rheumatoid arthritis (RA) starts at a younger age in cities with a lower latitude (closer to both sides of the equator). This consistent finding still remains to be explained. It has been hypothesized that latitude is a proxy for presence of genetic (eg. ACPA) and environmental risk factors (eg. smoking) for RA onset. Objectives To study how age at RA onset varies with latitude worldwide and to what extent patient and country level factors explain this variability. Methods RA patients from the worldwide METEOR registry were included. Age at diagnosis as a proxy for age at RA onset, measured at the patient level, was the main outcome. The explanatory variable was the absolute value of latitude, measured as the latitude of the hospital (hospital level). Patient factors considered potentially relevant were gender, RF and ACPA positivity, smoking status, symptom duration (months), year of first visit and BMI (all patient level). Country level factors were socioeconomic indicators (physician density, health expenditure, life expectancy, GDP per capita and gross enrolment in secondary school), derived from country statistics. We hypothesized that both patient and country level factors explain (ie. mediate) a relationship between latitude and age at diagnosis (Figure 1). We applied Bayesian multilevel linear structural equations models, which not only quantify effects at multiple levels but also disentangle at which level the effects take place. For example, they can differentiate whether hospital or country latitude affects age at diagnosis. We examined: 1. the total effect of latitude on age at diagnosis at hospital and country level (Main model); 2. the amount of the total effect that is mediated by patient factors at the patient and hospital level (Model A); and 3. the amount of the total effect that is mediated by country factors at the country level (Model B). In each model we disentangle the effect in different measurement levels. For example, a patient level variable can vary at the patient, hospital and country level. Results We included 39 782 patients nested in 94 hospitals nested in 17 countries. The mean age at diagnosis per country ranged from 39 to 55 years. The study spanned a range of latitude between 9.9 and 55.8 degrees (ie. from Nigeria to the United Kingdom). In the main model, we confirmed the association between latitude and age at diagnosis and found that it only occurred at the country level (not at the hospital level). Per degree increase in country latitude, the average age at diagnosis per country increased by 0.23 years (95% credibility interval 0.07; 0.40). At the hospital level however, this effect was negligible: β= 0.040 (-0.16; 0.31). Associations between latitude and several patient factors were found at the country level, but these patient factors only associated with age at diagnosis at the patient level, not at the country (or hospital) level (Model A). This means patient-factors did not explain the association between latitude and age at diagnosis at the country level (main effect changed from 0.23 before to 0.37 after inclusion of patient factors). In model B latitude associated with most country factors (except GDP per capita). Even though none of these variables separately were significantly associated with age at diagnosis, inclusion of the set of country level factors reduced the country level effect of latitude on age at diagnosis from 0.23 to almost zero: β=-0.033 (-0.51; 0.37). Sensitivity analyses with age at symptom onset as outcome provided similar results. Conclusion Patients living close at the equator indeed get RA far earlier than those living closer to the poles. We here suggest that, rather than due to variation in patients’ characteristics, this latitude gradient is a country level phenomenon explained by indicators of countries’ socioeconomic status, and not by patient specific genetic or environmental factors. This big data analysis in a worldwide prevalence cohort provides a direct link between countries’ levels of welfare and the onset of RA. Disclosure of Interests Sytske Anne Bergstra Grant/research support from: Pfizer, Alexandre Sepriano Speakers bureau: Novartis, Consultant of: UCB, Arvind Chopra: None declared, Lai-Ling Winchow: None declared, David Vega-Morales: None declared, Karen Solomon-Escoto: None declared, Xanthe Matthijssen: None declared, Robert B.M. Landewé Shareholder of: Director of Rheumatology Consultancy BV, Consultant of: Honoraria from AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Eli-Lilly, Novartis, Pfizer, UCB Pharma.